Production subsidies for renewable energy, such as solar or wind power, are rationalized by their environmental benefits. Subsidizing these projects allows clean, renewable technologies to produce electricity that otherwise would have been produced by dirtier, fossil-fuel power plants. In this paper, I quantify the emissions offset by wind power for a large electricity grid in Texas using the randomness inherent in wind power availability. When accounting for dynamics in the production process, the results indicate that only for high estimates of the social costs of pollution does the value of emissions offset by wind power exceed cost of renewable energy subsidies.

[T]he quantity of emissions offset by wind power will depend crucially on which generators reduce their output. This paper introduces an approach to empirically measure the environmental contribution of wind power resulting from these production offsets.

Utilizing information on production decisions in 15-minute intervals on the Texas electricity grid, I estimate the response of each generator to exogenous changes in wind power. Realizing that wind power production is not completely random, I control for factors that may drive the incentives for electricity production, which may also be correlated with wind power production. The resulting quasi-experimental residual variation is then used to identify a substitution coefficient for each generator on the grid. Importantly, I show that failing to control for impact that wind has on the dynamic process of electricity production overestimates the production offsets. These production offsets then translate directly into emission offsets using generator emission rates.

Estimated offsets can be valued by appealing to estimates from the literature on the marginal damage costs of emissions. This allows a direct comparison between the value of short run offset emissions with the cost of subsidies which drive investment in wind farms. …

Rather than using an engineering or marginal cost stack approach which calculates emission offsets given a set of parameters, I use an econometric approach to estimate the emissions offset by wind power from observed output decisions. This econometric model exploits random and exogenous changes in the output of wind farms to identify the generating substitutes of wind power from observed, rather than simulated, behavior in such a way that allows for a high degree of heterogeneity among generators. I use a flexible, reduced form model which respects the dynamic constraints of generators, incorporates firms’ reactions to uncertainty, and admits market power which may exist in certain states of the market. It does not require proprietary data on generators, but relies only on publicly available generator output and characteristics. …

The estimation approach used in this paper exploits the randomness and exogeneity of wind patterns to identify the average reduction in output for each generator on the grid due to wind power production. However, as previously highlighted, the diurnal and seasonal patterns of wind are not uncorrelated with other incentives for production by conventional generators. In this model, I will need to control for factors that affect a conventional producer’s decision to generate electricity, which may also be correlated with wind power production. In particular, one needs to account not only for static, but also for dynamic factors in the generators production decision. …

Since wind power is not produced near demand centers, it could be that the offsets are less than one-to-one due to transmission line losses. …

There is some concern that applying average emission rates to offset production estimates may not give an accurate estimate of offset emissions. A generator’s emission rate, although relatively constant for most technologies, can vary as a function of output level of the plant. Generators generally operate most efficiently when operating steadily near maximum capacity; operating at partial capacity may increase emission rates. Emission rates can also change during ramping. Periods when a generator is ramping up will have higher than average emission rates. Likewise, emission rates drop when a generator is ramping down, though the effect is not necessarily symmetric. This emission “bias” is documented in the engineering literature. Katzenstein and Apt (2009) measure the effect of the output level and ramping on emissions for two types of natural gas generators. From an engineering standpoint, they show that actual emission offsets from wind power may be 20–50 percent lower than those implied when using average emission rates. This bias is increasing in the level of penetration of wind power as hypothetical gas generators are forced to operate at lower and lower capacity levels and incur more ramping. …

[I]f a pollutant is already subject to optimal regulation, then offsets yield no additional value. In addition, for emissions regulated under a binding cap-and-trade program, offset emissions do not imply a reduction in total emissions regardless of the optimality of the regulation. Emissions offset at one facility result in pollution permits being freed up for use elsewhere. For this reason, pollutants regulated under cap-and-trade systems, such as SO₂ and NOx, offsets may not have environmental benefits. …

A large body of literature exists on the estimated damages of CO₂ emissions. Tol (2005) reviews the literature, which estimates the social costs of CO2, and concludes that the costs imposed by CO₂ are less than $50/ton and probably significantly lower than that. The median marginal damage costs of CO₂, as found in papers published in peer-reviewed journals, was $14/ton (Tol 2005).

More recently, the US government has compiled estimates on the social cost of carbon for use in regulatory analyses. The Interagency Working Group on Social Cost of Carbon compiled the report which estimates the monetized damages associated with an incremental increase in carbon emissions in a given year. The group selected four values which are based on a collection of integrated assessment models, at different discount rates. The values for the social cost of carbon produced by the report were $5, $21, and $35, per ton of CO₂ for the year of 2010, with $21 being the “central” value. …

[E]missions of SO₂ are regulated at every power plant. This, and the fact that there are negligible estimated offsets, implies that no benefits will accrue from SO₂ offsets in Texas.

For the value of offset NOx, … I use estimates from Muller and Mendelsohn (2011), which use an integrated assessment model to calculate spatially differentiated marginal damage costs. In Texas, the estimated costs are in the range of $100–$2,000/ton of NOx. …

[T]he value of emissions offset by wind power ranges from less than $3/MWh in the low value scenario to less than $10/MWh for middle-range estimates to a little more than $17/MWh for the higher end of marginal damage costs. …

[T]he emissions benefits of wind power fail to exceed the $20/MWh subsidy even for higher estimates of marginal damage costs. The social cost of carbon would have to be greater than $42 for the benefits of the subsidy to outweigh its costs based on carbon offsets alone. Note that even then this result does not imply that wind power would be the lowest cost method of reducing CO₂ emissions; it is almost certainly not.

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